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Subject offerings of new and developing areas of knowledge in electrical and computer engineering intended to augment the existing curriculum. See Class Schedule or departmental course information for topics and prerequisites. Course Information: May be repeated in the same or separate terms if topics vary.

This course develops the foundations of generative models, covering the four main pillars: variational inference (VAE), diffusion models (Diffusion), generative adversarial networks (GAN), and normalizing flows (Flow). Although mostly mathematical, the treatment of topics will be from first principles, often revisiting core undergraduate material (in linear algebra, probability, optimization), and visualizing them in the context of neural networks. Each topic will close with recent research papers and their corresponding applications. Please visit the course website here: https://rrc-uiuc.notion.site/gen-models-fa25